version: '3.8'

services:
  neurosymbolic-agent:
    build:
      context: .
      dockerfile: Dockerfile
      target: base  # Use 'cpu-base' for CPU-only
    container_name: neurosymbolic-agent
    volumes:
      # Mount data directories for persistence
      - ./data:/app/data
      - ./logs:/app/logs
      - ./models:/app/models
      - ./cache:/app/cache
      - ./configs:/app/configs
    environment:
      # LLM Backend Configuration
      - LLM_BACKEND=local
      - LOCAL_MODEL_NAME=auto
      - ALLOW_HEURISTIC_FALLBACK=true
      - CONFIDENCE_THRESHOLD=0.75
      - ENABLE_TELEMETRY=true
      
      # Memory Configuration
      - VECTOR_DB_TYPE=sqlite
      - VECTOR_DB_DIR=/app/data/vector_db
      
      # Logging
      - LOG_LEVEL=INFO
      - LOG_TO_CONSOLE=true
      
      # Optional: Cloud LLM API Keys
      # - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
      # - OPENAI_API_KEY=${OPENAI_API_KEY}
    
    # GPU support (uncomment if using NVIDIA runtime)
    # deploy:
    #   resources:
    #     reservations:
    #       devices:
    #         - driver: nvidia
    #           count: 1
    #           capabilities: [gpu]
    
    ports:
      - "7860:7860"
    
    stdin_open: true
    tty: true
    
    restart: unless-stopped
    
    networks:
      - agent-network

  # Optional: Jupyter notebook service
  jupyter:
    build:
      context: .
      dockerfile: Dockerfile
      target: base
    container_name: neurosymbolic-jupyter
    volumes:
      - ./data:/app/data
      - ./logs:/app/logs
      - ./models:/app/models
      - ./cache:/app/cache
      - ./configs:/app/configs
      - ./notebooks:/app/notebooks
    environment:
      - LLM_BACKEND=local
      - LOCAL_MODEL_NAME=auto
    command: >
      sh -c "pip install jupyter notebook ipywidgets && 
             jupyter notebook --ip=0.0.0.0 --port=8888 
             --no-browser --allow-root --NotebookApp.token=''"
    ports:
      - "8888:8888"
    networks:
      - agent-network

networks:
  agent-network:
    driver: bridge

volumes:
  data:
  logs:
  models:
  cache: